System and method for detecting anomalies along telecommunication lines

ABSTRACT

An anomaly detection system comprises an echo canceler and anomaly detection logic. The echo canceler has a plurality of taps respectively associated with a plurality of tap coefficients. The anomaly detection logic is configured to determine a difference between a new tap coefficient associated with one of the taps and a previous tap coefficient associated with the one tap. The anomaly detection logic is configured to perform a comparison between the difference and a threshold and to detect an anomaly along a telecommunication line based on the comparison.

RELATED ART

Telecommunication lines, such as a digital subscriber line (DSL), forexample, usually comprise sections of wire that have been joinedtogether to form a data path from one location to another (e.g., fromcommunication equipment at a central office to communication equipmentat a customer premises). A point where two sections of atelecommunication line are joined is often referred to as a “splice.” Informing a splice, the end of one section is usually wrapped around orotherwise joined to an end of another section, and the two joined endsmay be soldered in an effort to ensure that the splice does not loosen.

In this regard, it is generally desirable for the two joined sectionends forming a splice to remain in a tightly joined position in aneffort to minimize the resistivity of the splice. However, over time, asplice may become degraded (e.g., loosen) such that the resistivity ofthe splice fluctuates. Such resistivity fluctuation can significantlydisrupt communication occurring over the telecommunication line thatincludes the splice.

Thus, when a splice becomes significantly degraded, it may be desirablefor a technician to locate and repair the degraded splice in an effortto improve communication occurring over the telecommunication line thatincludes the degraded splice. However, locating such a degraded splicecan be difficult. In particular, disruption of communication occurringover a telecommunication line may be caused by a variety of factors inaddition to or in lieu of degraded splices. Thus, diagnosing acommunication problem attributable to a degraded splice can beproblematic. Further, many telecommunication lines extend for very longdistances (e.g., on the order of several miles) and are often buried inthe ground. Accordingly, even when a communication problem is correctlydiagnosed as attributable to a degraded splice along a telecommunicationline, locating the degraded splice can be difficult and expensive.

Thus, a heretofore unaddressed need exists in the art for improvedsystems and methods of detecting and locating degraded splices and othertypes of anomalies along a telecommunication line.

SUMMARY OF THE INVENTION

Generally, embodiments of the present invention provide systems andmethods for detecting anomalies along telecommunication lines.

An anomaly detection system in accordance with one exemplary embodimentof the present invention comprises an echo canceler and anomalydetection logic. The echo canceler has a plurality of taps respectivelyassociated with a plurality of tap coefficients. The anomaly detectionlogic is configured to determine a difference between a new tapcoefficient associated with one of the taps and a previous tapcoefficient associated with the one tap. The anomaly detection logic isconfigured to perform a comparison between the difference and athreshold and to detect an anomaly along a telecommunication line basedon the comparison.

An anomaly detection system in accordance with another exemplaryembodiment of the present inventions comprises an echo canceler andanomaly detection logic. The echo canceler has a plurality of tapsrespectively associated with a plurality of tap coefficients. Theanomaly detection logic is configured to determine when at least one ofthe tap coefficients fluctuates by at least a specified amount and todetect an anomaly along a telecommunication line based on a detection,by the logic, that the at least one tap coefficient fluctuated by atleast the specified amount.

An anomaly detection system in accordance with yet another exemplaryembodiment of the present invention comprises an echo canceler andanomaly detection logic. The echo canceler has a plurality of tapsrespectively associated with a plurality of tap coefficients. Theanomaly detection logic is configured to establish a set of baseline tapcoefficients based on the tap coefficients. The anomaly detection logicis configured to compute differences between new tap coefficients of theecho canceler and the baseline tap coefficients and to detect an anomalyalong a telecommunication line based on the differences.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention can be better understood with reference to the followingdrawings. The elements of the drawings are not necessarily to scalerelative to each other, emphasis instead being placed upon clearlyillustrating the principles of the invention. Furthermore, likereference numerals designate corresponding parts throughout the severalviews.

FIG. 1 is a block diagram illustrating a transceiver that employs ananomaly detection system in accordance with an exemplary embodiment ofthe present disclosure.

FIG. 2 is a block diagram illustrating the transceiver of FIG. 1 coupledto a remote transceiver via a telecommunication line.

FIG. 3 is a graph illustrating differential tap coefficient values of atransceiver's echo canceler (EC) when the resistance of a point along atelecommunication line approximately 0 feet from the transceiver isvaried from 0 to 5 Ohms, 0 to 10 Ohms, 0 to 20 Ohms, 0 to 50 Ohms, and 0to 100 Ohms.

FIG. 4 is a graph illustrating differential tap coefficient values of atransceiver's echo canceler when the resistance of a point along atelecommunication line approximately 4000 feet from the transceiver isvaried from 5 to 0 Ohms, 10 to 0 Ohms, 20 to 0 Ohms, 50 to 0 Ohms, and100 to 0 Ohms.

FIG. 5 is a block diagram illustrating the anomaly detection system ofFIG. 1.

FIGS. 6 and 7 depict a flow chart illustrating an exemplary methodologythat may be used by the anomaly detection system of FIG. 1.

FIG. 8 is a flow chart illustrating another exemplary methodology thatmay be used by the anomaly detection system of FIG. 1.

DETAILED DESCRIPTION

The present disclosure generally pertains to systems and methods fordetecting anomalies, such as degraded splices, for example, along atelecommunication line. An anomaly detection system in accordance withone exemplary embodiment of the present disclosure analyzes the tapcoefficients of an echo canceler to detect a line anomaly. In thisregard, according to known or future-developed echo cancellationtechniques, the echo canceler generates tap coefficients that are usedto generate an echo cancellation signal for removing echoes from signalscommunicated over a telecommunication line coupled to the echo canceler.The anomaly detection system analyzes the tap coefficients of the echocanceler over time and determines when a tap coefficient significantlyfluctuates. When the anomaly detection system identifies a significantlyfluctuating tap coefficient, it may provide an indication that ananomaly, such as a degraded splice, exists along the telecommunicationline at a distance corresponding to the fluctuating tap coefficient.

FIG. 1 depicts an anomaly detection system 20 in accordance with anexemplary embodiment of the present disclosure. As shown by FIG. 1, theanomaly detection system 20 may reside within a transceiver 23 that iscoupled to and communicates over a telecommunication line 25, such as adigital subscriber line (DSL), for example. However, it should be notedthat one or more components of the detection system 20 may be locatedexternal to the transceiver 23, if desired.

As shown by FIG. 2, the transceiver 23 may be coupled to a remotetransceiver 27 via the telecommunication line 25. In one example, thetransceiver 23 may reside at a central office of a communicationnetwork, and the remote transceiver 27 may reside at a customerpremises. In another example, the transceiver 23 may reside at acustomer premises, and the remote transceiver 27 may reside at a centraloffice. Other locations for the transceivers 23 and 27 are possible inother embodiments.

As shown by FIG. 1, the transceiver 23 comprises a transmitter 31 and areceiver 33. The transmitter 31 transmits a digital data signal to adigital filter 35, which filters the digital data signal and provides afiltered digital signal to a digital-to-analog (D/A) converter 38. TheD/A converter 38 converts the filtered digital signal into an analogsignal, which is filtered by an analog filter 41. This filtered analogsignal is then applied to the telecommunication line 25 via a hybridnetwork 44 and a line-coupling transformer 46.

An analog signal on the telecommunication line 25 is coupled throughtransformer 46 and hybrid network 44 and is applied to an analog filter52, which filters the received analog signal and provides a filteredanalog signal to an analog-to-digital (A/D) converter 54. The A/Dconverter 54 converts the filtered analog signal into a digital signal,which is filtered by a digital filter 57. A differential summer 59combines this filtered digital signal with an echo cancellation signalfrom an echo canceler 63 in order to cancel, from the filtered digitalsignal, echoes of signals transmitted by the transceiver 23 over thetelecommunication line 25. The combined signal from the differentialsummer 59 is then received by the receiver 33.

Various known or future-developed echo cancelers may be used toimplement the echo canceler 63 of FIG. 1. In one exemplary embodiment,the echo canceler 63 is implemented as a linear adaptive finite impulseresponse (FIR) filter that uses a least mean squared (LMS) algorithm orother known or future-developed adaptive FIR algorithm to provide anecho cancellation signal that minimizes the error of the combined signaloutput from the differential summer 59. In other embodiments, othertypes of echo cancelers may be employed.

Using a plurality of taps 64 spaced along a tap delay line, the echocanceler 63 respectively multiplies tap coefficients 66 to delayedreplicas of a digital input signal from transmitter 31 in order tooutput an appropriate echo cancellation signal. In this regard, each tap64 is associated with a different tap coefficient, which may beadaptively changed in order control the shape of the echo cancellationsignal. In general, to better suppress echoes, the tap coefficients arecontrolled such that the shape of the echo cancellation signal closelyresembles or matches the shape of the echoes included in the signaloutput by the digital filter 57. Techniques for controlling the tapcoefficients of an echo canceler such that the echo canceler outputs anappropriate echo cancellation signal are well-known in the art.

Changes in the resistivity of the telecommunication line 25 induceschanges in the tap coefficients of the echo canceler 63 if the echocanceler 63 is to maintain adequate echo cancellation. Indeed, FIGS. 3and 4 show test results of simulating a degraded splice at distances ofapproximately 4000 feet from a transceiver 23. In this regard, to plot adifferential tap coefficient value for a particular tap 64, the tapcoefficient for the tap 64 is read and stored. Then, the resistance of apoint along the telecommunication line 25 is varied from a firstresistance to a second resistance. The tap coefficient for the tap 64 isthen read and subtracted from the previously read tap coefficient. Thisdifference is then plotted. The foregoing may be performed for each tapcoefficient, and a curve may then be fitted to each plotted differentialassociated with the same resistivity change.

In FIG. 3, the point of varied resistivity is located close to (e.g.,approximately 0 feet from) the end of the telecommunication line 25 thatis coupled to the transceiver 23. In FIG. 4, the point of variedresistivity is located approximately 4000 feet from the transceiver 23.In addition, in FIG. 3, the curves were obtained by varying theresistance of the line 25 from 0 to 5 Ohms, 0 to 10 Ohms, 0 to 20 Ohms,0 to 50 Ohms, and 0 to 100 Ohms. In FIG. 4 the curves were obtained byvarying the resistance of the line 25 from 5 to 0 Ohms, 10 to 0 Ohms, 20to 0 Ohms, 50 to 0 Ohms, and 100 to 0 Ohms.

As can be seen by comparing FIGS. 3 and 4, a fluctuation in theresistivity of the telecommunication line 25 will have a greater effecton certain ones of the tap coefficients depending on the location of theresistivity fluctuation along the telecommunication line 25. Thus, aline anomaly, such as a degraded splice, that changes the resistance ofa point along a telecommunication line can be detected and located bydetermining which of the tap coefficients are affected by the resistancefluctuations. Indeed, each tap coefficient can be correlated with aparticular point along the telecommunication line 25 such that, if adetermination can be made that a tap coefficient fluctuates due to aline anomaly, then it follows that the line anomaly is close inproximity to the correlated point. Such an approach can be used toimplement an anomaly detection system and methodology as will bedescribed in more detail hereinbelow.

As shown by FIG. 1, the anomaly detection system 20 comprises anomalydetection logic 70 that analyzes the tap coefficients 66 of the echocanceler 63 and detects anomalies, such as degraded splices, along thetelecommunication line 25 based on the tap coefficients 66. The anomalydetection logic 70 can be implemented in software, hardware, or acombination thereof. In an exemplary embodiment illustrated in FIG. 5,the anomaly detection logic 70, along with its associated methodology,is implemented in software and stored in memory 75.

Note that the anomaly detection logic 70, when implemented in software,can be stored and transported on any computer-readable medium for use byor in connection with an instruction execution system, apparatus, ordevice, such as a computer-based system, processor-containing system, orother system that can fetch and execute instructions. In the context ofthis document, a “computer-readable medium” can be any means that cancontain, store, communicate, propagate, or transport a program for useby or in connection with the instruction execution system, apparatus, ordevice. The computer readable-medium can be, for example but not limitedto, an electronic, magnetic, optical, electromagnetic, infrared, orsemiconductor system, apparatus, device, or propagation medium. Notethat the computer-readable medium could even be paper or anothersuitable medium upon which the program is printed, as the program can beelectronically captured, via for instance optical scanning of the paperor other medium, then compiled, interpreted or otherwise processed in asuitable manner if necessary, and then stored in a computer memory.

The exemplary embodiment of the anomaly detection system 20 depicted byFIG. 5 comprises at least one conventional processing element 77, suchas a digital signal processor (DSP) or a central processing unit (CPU),that communicates to and drives the other elements within the system 20via a local interface 79, which can include at least one bus.Furthermore, the system 20 may comprise at least one timer 81 that maybe used by the anomaly detection logic 70, as will be described in moredetail hereafter. The timer 81 may be implemented in hardware or acombination of hardware and software.

As shown by FIG. 5, a set of predefined tap thresholds 85 is stored inmemory 75. Each tap threshold is associated with a different one of theecho canceler taps 64 (FIG. 1). The value of a tap threshold isestablished such that there is high likelihood of an anomaly, such as adegraded splice, existing at or close to a correlated point ontelecommunication line 25 if a change in the value of the tapcoefficient for the associated tap 64 exceeds the threshold.

Note that the values of the tap thresholds may be established based onFIGS. 3 and 4. For example, assume that it is desirable to detect adegraded splice if the resistivity of a point of the telecommunicationline 25 fluctuates by more than 50 Ohms in a short amount of time. Insuch an example, the 50 Ohm curves of FIGS. 3 and 4 may be used toestablish the tap threshold for a particular tap 64. In this regard, thetap threshold for a particular tap 64 may be assigned the peak (eitherpositive or negative) tap differential value associated with theparticular tap 64 and plotted in the 50 Ohm curves for either of thegraphs depicted by FIGS. 3 and 4. As an example, noting that each tap 64is assigned a different identifier number ranging from 20 to 50 in FIGS.3 and 4, the tap 64 having identifier number 28 appears to be associatedwith a peak tap coefficient differential close to the value of 4000 forthe 50 Ohm curves of FIGS. 3 and 4. Thus, the tap threshold associatedwith the foregoing tap 64 may have a value of 4000.

During operation, the anomaly detection logic 70 reads a set of tapcoefficients 66 from the echo canceler 63 and stores this set of tapcoefficients, referred to hereafter as “baseline tap coefficients 88,”in memory 75 (FIG. 5). Generally, if there are no anomalies present onthe telecommunication line 25, then the tap coefficients in the echocanceler 63 should not significantly vary except for gradual variationsover time due to temperature fluctuations. Moreover, the anomalydetection logic 70 periodically reads the current tap coefficients fromthe echo canceler 63 and compares the current tap coefficients to thebaseline tap coefficients. In particular, each baseline tap coefficientand current tap coefficient is associated with a different echo cancelertap 64. As used herein, the baseline tap coefficient and current tapcoefficient that are both associated with the same echo canceler tapwill be referred to hereafter as a “tap pair.” For each tap pair, theanomaly detection logic 70 subtracts the current tap coefficient fromthe baseline tap coefficient. In other words, the anomaly detectionlogic 70 computes the difference between the coefficients of the tappair.

After computing the tap pair difference, the anomaly detection logic 70compares the tap pair difference to the corresponding tap threshold(i.e., the tap threshold associated with the same echo canceler tap 64as the tap pair) stored in memory 75. If the absolute value of the tappair difference exceeds the absolute value of the corresponding tapthreshold, then the anomaly detection logic 70 provides an anomalyindication. In this regard, if the absolute value of the tap pairdifference exceeds the absolute value of the corresponding tapthreshold, then the tap coefficient 66 of the associated tap 64 hassignificantly changed over time (i.e., between reading of the baselinetap coefficient of the tap pair and the current tap coefficient of thetap pair). Such a significant change may indicate that an anomaly, suchas a degraded splice, for example, is on the telecommunication line 25at a location corresponding to the tap pair and its associated tap 64.Thus, the anomaly indication provided by the anomaly detection logic 70may indicate that an anomaly exists on the telecommunication line 25 atthe location corresponding to the tap coefficient pair on which theanomaly indication is based.

To help increase the accuracy of the anomaly detection performed by thelogic 70, the logic 70 may track a history of its anomaly indications.In this regard, the anomaly detection logic 70 may maintain diagnosticinformation 92 (FIG. 5) indicative of the history of the anomalydetections provided by the logic 70. In one embodiment, the diagnosticinformation 92 comprises a histogram having a plurality of values inwhich each histogram value corresponds to a different echo canceler tap64. Each time the difference of a tap pair associated with the tap 64(i.e., the difference of a tap's current and baseline tap coefficients)exceeds the corresponding tap threshold, the anomaly detection logic 70may increment the corresponding histogram value. Thus, each histogramvalue is essentially a running sum of the number of anomaly indicationsprovided by the logic 70 for a particular one of the taps 64. Generally,the higher a tap's corresponding histogram value, the more likely it isthat an anomaly exists on the telecommunication line 25 at the locationcorresponding to the tap 64. Thus, by analyzing the histogram values, itis possible to identify locations on the telecommunication line 25 whereanomalies exist.

To help increase the effectiveness of the histogram as a tool toestimate locations of anomalies along the telecommunication line 25, thebaseline tap coefficients may be updated from time to time. To update abaseline tap coefficient, the current tap coefficient associated withthe same tap 64 as the baseline tap coefficient may be read by theanomaly detection logic 70 and used to replace the baseline tapcoefficient. By periodically updating the baseline tap coefficients inthis manner, gradual variations in the tap coefficients due to gradualtemperature fluctuations can be accommodated such that the gradualvariations in the coefficient taps due to temperature fluctuations donot cause many false anomaly indications.

In addition, a better histogram may be defined by updating one or morebaseline tap coefficients for each occurrence of an anomaly indication.In this regard, if the anomaly detection logic 70 determines that a tappair difference exceeds the corresponding tap threshold, then inaddition to providing an anomaly indication (e.g., in addition toincrementing the corresponding histogram value), the anomaly detectionlogic 70 may also update the baseline tap coefficients by replacing thebaseline tap coefficients with the current tap coefficients. In analternative embodiment, the baseline tap coefficients may be updatedeach time new current tap coefficients are read from the echo canceler63 regardless of whether any anomaly indications based on the newcurrent tap coefficients are generated. Other embodiments that updatethe baseline tap coefficients in different manners are also possible.

There are various methodologies that may be used to detect atelecommunication line anomaly based on whether a particular tapcoefficient of an echo canceler significantly fluctuates over time.Described hereafter are two cases that these methodologies address. Thefirst case (“case one”) is when the severity of the anomaly is such thatit causes the transceiver to have degraded performance, and possiblyeven an occasional loss of synchronization resulting in retraining ofthe transceiver. The second case (“case two”) is when the severity ofthe anomaly prevents synchronization altogether. FIGS. 6 and 7 depict anexemplary methodology that may be employed by the anomaly detectionlogic 70 in order to detect an anomaly, such as a degraded splice, oftelecommunication line 25. The methodology of FIGS. 6 and 7 addressesthe lower severity anomaly case identified as case one above.

For the purposes of illustration, assume that the anomaly detectionlogic 70 is configured to track the coefficients of n number taps of theecho canceler 63, where n is any positive integer. Further assume that aparticular one of the taps 64, referred to hereafter as “tap a,”corresponds to a location on the telecommunication line 25 that is adistance “d” (FIG. 2) from the transceiver 23. In this regard, a changein the contact resistance of the telecommunication line 25 at a distanced from the transceiver 23 causes the tap coefficient of tap a to change.For the purposes of illustration, assume that a significantly degradedsplice is located at distance d from the transceiver 23, thereby-causingthe contact resistance of the line 25 at distance d from the transceiver23 to significantly fluctuate over time. Also assume that there are noother degraded splices or other types of line on the telecommunicationline 25.

Similar to conventional transceivers, the transceiver 23 of FIG. 1 mayestablish communication settings, such as an initial set of tapcoefficients 66, for example, in a training mode and then communicatedata in a data mode that follows the training mode. In the embodimentdepicted by FIGS. 6 and 7, block 101 shows the initialization of thetimer 81 (FIG. 5), thermal tracking count, maximum thermal SEV (SignalError Value), minimum thermal SEV, and detection SEV, which will all bediscussed later. Note that the thermal tracking count, the maximum SEV,minimum thermal SEV, and detection SEV are all variables. In oneexemplary embodiment, the thermal tracking count is initialized to avalue of four, and the maximum SEV is initialized to a value of zero.Further, the detection SEV and the minimum SEV are both respectivelyinitialized to their highest possible value. For example, if an 8-bitvalue is used to represent the detection SEV, then this variable isinitialized to a value of two-hundred-fifty-five. Similarly, if an 8-bitvariable is used to represent the minimum SEV, then this variable isalso initialized to a value of two-hundred-fifty-five (255). Note thatthe foregoing variables may be initialized to other values in otherembodiments.

In addition to initializing the aforedescribed variables, the anomalydetection logic 70 initializes the timer 81 such that it periodicallyexpires. In the exemplary embodiments described herein, it will beassumed that the timer 81 is initialized to expire every thirty seconds,although other timing cycles may be employed in other embodiments.

Block 101 also shows the transceiver 23 transitioning into the data modefrom the training mode. In the data mode, steps are taken to help ensurethat the baseline tap coefficients 88 used to detect line anomalies aredefined during reliable time periods (e.g., during periods that aresubstantially free of communication errors occurring over line 25).Exemplary techniques for achieving the foregoing will now be describedin detail.

In this regard, the anomaly detection logic 70 sets the detection SEV toa value indicative of an amount of error recently occurring across theline 25. For example, as described above, the timer 81 is configured toperiodically expire (e.g., every 30 seconds in the instant embodiment),and the detection SEV may be the minimum signal-to-noise ratio detectedduring the last cycle of timer 81 (i.e., between the last consecutiveexpirations of the timer 81). In another embodiment, the detection SEVmay be an average signal-to-noise ratio detected during the last cycleof timer 81. In yet another embodiment, the detection SEV may be thetotal number of bit errors detected during the last cycle of timer 81.In essence, the detection SEV can be any value that is indicative of anamount of error that recently occurred over line 25, and other types ofvalues for the detection SEV not specifically discussed herein may beused in other embodiments.

For the purposes of illustration, assume hereafter that the detectionSEV is a minimum signal-to-noise ratio (SNR) detected sinceinitialization of the detection SEV in either block 101, 117, or 143.Therefore, a lower value for the detection SEV indicates that a highernumber of errors or level of noise recently occurred over thetelecommunication line 25. Also assume that the minimum thermal SEV isthe minimum signal-to-noise ratio for the line 25 detected since thelast initialization of this variable in block 101 or 143, and assumethat the maximum thermal SEV is the maximum signal-to-noise ratio forthe line 25 detected since the last initialization of this variable inblock 101 or 143. Other embodiments may define the minimum thermal SEVand the maximum thermal SEV variables differently.

To establish the foregoing variables, the anomaly detection logic 70determines the current signal-to-noise ratio of the line 25 in block107. This signal-to-noise ratio may be calculated at the transceiver 23via known or future-developed techniques and provided to logic 70. Ifthe current signal-to-noise ratio is less than the value of thedetection SEV, then the anomaly detection logic 70 sets the detectionSEV equal to the current signal-to-noise ratio, as shown by blocks 108and 109. If the current signal-to-noise ratio is equal to or greaterthan the value of the detection SEV, then the anomaly detection logic 70does not change the value of the detection SEV. Thus, the detection SEVis equal to the minimum signal-to-noise ratio detected since the lastinitialization of the detection SEV in block 101 or 117.

In block 110, the anomaly detection logic 70 compares the currentsignal-to-noise ratio to the minimum thermal SEV. If the currentsignal-to-noise ratio is less than the value of the minimum thermal SEV,the anomaly detection logic 70 sets the minimum thermal SEV equal to thecurrent signal-to-noise ratio, as shown by block 111. If the currentsignal-to-noise ratio is equal to or greater than the value of theminimum thermal SEV, then the anomaly detection logic 70 does not changethe value of the minimum thermal SEV. Thus, the minimum thermal SEV isequal to the minimum signal-to-noise ratio detected since the lastinitialization of the minimum thermal SEV in block 101 or 143.

In block 112, the anomaly detection logic 70 compares the currentsignal-to-noise ratio to the maximum thermal SEV. If the currentsignal-to-noise ratio is greater than the value of the maximum thermalSEV, the anomaly detection logic 70 sets the maximum thermal SEV equalto the current signal-to-noise ratio, as shown by block 113. If thecurrent signal-to-noise ratio is equal to or less than the value of themaximum thermal SEV, then the anomaly detection logic 70 does not changethe value of the maximum thermal SEV. Thus, the maximum thermal SEV isequal to the maximum signal-to-noise ratio detected since the lastinitialization of the maximum thermal SEV in block 101 or 143.

On the timer 81 expires, the anomaly detection logic 70, in block 114,compares the detection SEV to a value, referred to hereafter as the“signal error threshold” or “SET.” The signal error threshold comparedin block 114 is preferably set to a value such that the detection SEV isgreater than this threshold when reliable communication has continuouslyoccurred since the last initialization of the detection SEV in blocks101, 117, or 143. In this regard, if the data communication occurringover line 25 has too many errors due to severe line anomalies or othertypes of communication problems, then the anomaly test results duringsuch times of significant communication errors may be unreliable. Inthis regard, during periods of significant communication error acrossline 25, it is unlikely that the tap coefficients 66 of the echocanceler are sufficient for properly cancelling the echo of thetransmitted signal, and anomaly tests based on the tap coefficients 66may not be reliable. Moreover, the general purpose of the comparisonperformed in block 114 is to ensure that an unreasonable amount of erroris not present on the line 25 before testing the line 25 for anomalies.Although other values may be used, the signal error threshold in oneexemplary embodiment is equal to 3 decibels (dB).

If the detection SEV is not greater than the signal error threshold,then a “no” determination is made in block 114. In such a scenario, theanomaly detection logic 70, in block 117, initializes the detection SEVto its maximum possible value, as described above with reference toblock 101, and the anomaly detection logic 70 then repeats blocks105-113 until the next expiration of timer 81.

When a “yes” determination is made in block 114, a relatively low numberof errors occurred during the last cycle of the timer 81. Thus, it islikely that the current tap coefficients 66 of the echo canceler 63 aresufficient to cancel the echo of the transmitted signal. These currenttap coefficients 66 are, therefore, valid for use in anomaly detection.Since a valid set of tap coefficients 66 now exists, the anomalydetection logic 70 decrements the thermal tracking count in block 115,and the echo canceler tap coefficients 66 are read and stored in block116. As will be described in more detail hereafter, the thermal trackingcount is used to ensure that periodic updates of the baseline tapcoefficients 88 occur, thereby accounting for gradual changes to the tapcoefficients 66 due to temperature fluctuations.

In block 118, the anomaly detection logic 70 determines whether abaseline set of echo tap coefficients 88 already exists. If a “no”determination is made, then the current echo tap coefficients 66 arestored as the baseline set of tap coefficients 88 in block 139, and thethermal tracking count is then reset or re-initialized to its startingvalue (e.g., four in the instant embodiment) in block 143. The maximumthermal SEV and minimum thermal SEV are also reset or re-initialized inblock 143. For illustrative purposes, assume that the tap coefficient oftap a has a value of one-thousand (1000) upon a “no” determination inblock 118. In such an example, the anomaly detection logic 70, in block139, stores a value of one-thousand (1000) in memory 75 as the baselinetap coefficient for tap a. Likewise the other tap coefficients 66 of theother taps 64 in existence may be used to establish the other baselinetap coefficients 88.

If a “yes” determination is made in block 118, then a set of baselinetap coefficients 88 already exists. In block 120 of FIG. 7, the anomalydetection logic 70 takes the current tap coefficients 66 that were readand stored in block 116 and compares these coefficients to the baselinetap coefficients 88 in an effort to detect line anomalies. Inparticular, for each tap 64, the logic 70 subtracts the tap's currentcoefficient from its corresponding baseline tap coefficient to compute adifference that indicates how much the tap's coefficient has changedsince the last occurrence of block 139.

In blocks 123 and 131, the anomaly detection logic 70 detects possibleline anomalies. In block 123, the anomaly detection logic 70 compareseach tap difference computed in block 120 to the corresponding tapthreshold stored in memory 75 (FIG. 5). If none of the tap differencesfrom block 120 respectively exceed the corresponding tap thresholds 85,then the coefficients of the taps 64 have not changed by an amount largeenough to indicate that a line anomaly may exist. If such a “no”determination is made in block 123, then the anomaly detection logic 70checks the thermal tracking count in block 127 to determine whether toupdate the baseline tap coefficients 88. If the thermal count equalszero, then the baseline tap coefficients 88 are updated in block 139 asdescribed above. The thermal tracking count, along with the maximumthermal SEV and minimum thermal SEV, are then reset or re-initialized inblock 143.

Note that utilization of the thermal tracking count, as described above,ensures that the baseline tap coefficients 88 are periodically updated,via block 139, thereby ensuring that gradual fluctuations in the tapcoefficients 66 due to temperature changes are accommodated. Byinitializing the thermal tracking count to a value of four in theinstant example, it can be ensured that the baseline tap coefficients 88are updated at least every four cycles of the timer 81 in which anacceptable error rate is present. Thus, in the instant embodiment whereeach cycle of timer 81 is thirty seconds, the thermal tracking count isused to ensure that the baseline tap coefficients 88 are updated atleast once every two minutes of substantially error free datatransmission.

If a “yes” determination is made in block 123, then at least one of thetap differences calculated in block 120 exceeds the corresponding tapthreshold 85 (i.e., the tap threshold 85 associated with the same tap64). This means that one or more of the tap coefficients 66 has changedby a significantly large amount indicating that a line anomaly mayexist.

Block 131 helps to reduce false detections of anomalies. To accuratelydetect degraded splices that can cause reduced transceiver performance,it is desirable for the thresholds 85 compared in block 123 to berelatively sensitive. Therefore, thermal changes and noise could cause afalse anomaly detection in block 123 when, in fact, no anomaly exists.However, a degraded splice exhibiting impedance changes of severity tocause performance problems will also cause degraded and fluctuatingsignal error values.

In block 131, the anomaly detection logic 70 compares the maximumthermal SEV and the minimum thermal SEV that have occurred since thelast occurrence of block 101 or 143. In particular, the difference ofthese two variables is calculated and compared to a SEV delta threshold(e.g., 5 dB). If the difference between the maximum thermal SEV andminimum thermal SEV does not exceed the SEV delta threshold, then it islikely that the change in tap coefficients detected in block 123 is dueto a problem other than a line anomaly, or it is likely that thetransceiver's data pump adequately responded to the problem. Thus, insuch an scenario, an anomaly indication is not provided (i.e., block 135is skipped), and the anomaly detection logic 70 checks the thermaltracking count 127 to see if it is time to update the baseline tapcoefficients 88 as previously described above.

If in block 131, the difference between the maximum thermal SEV andminimum thermal SEV does exceed the SEV delta threshold, then theanomaly detection is considered valid. The anomaly detection logic 70then stores an anomaly indication for the tap 64 whose threshold wasexceeded by the largest amount in block 123. In other embodiments, alltaps 64 whose thresholds were exceeded could be indicated.

As described above, the anomaly detection logic 70 may maintain ahistogram having a different running sum associated with each tap 64. Ifa tap 64 has the largest difference between its current coefficient andits baseline coefficient than the other taps 64 and if that differenceexceeds the corresponding tap threshold 85 in block 123, the anomalydetection logic 70, in block 135, may increment the tap's running sum.Thus, the running sum for a particular tap 64 indicates the total numberof times that the anomaly detection logic 70 detected a possible lineanomaly based on a comparison of the tap's coefficient in the echocanceler 63 with the tap's baseline coefficient stored in memory 75. Ingeneral, the higher the value of the tap's running sum, the more likelyit is that a line anomaly, such as a degraded splice, exists at thelocation of the line 25 corresponding to the tap 64.

To better illustrate the implementation of blocks 120, 123, 131, and135, assume that the line detection logic 70 reads a value ofone-thousand-seven-hundred (1700) for tap a in block 120. Also assumethe baseline tap coefficient of tap a is one-thousand (1000) and thecorresponding tap threshold for tap a is five-hundred (500). In such anexample, the absolute value of the difference between the tap's currentand baseline tap coefficients is seven-hundred (700), which exceeds thetap threshold of tap a. Therefore, block 123 would result in a “yes”decision. Assume all other taps are evaluated similarly and theirdifferences minus their thresholds are less than that of tap a. Alsoassume the maximum SEV was 17 dB and the minimum SEV was 6 dB. Then thedifference between these two is 11 dB, which is greater than the SEVdelta threshold of 5dB. Therefore, block 131 would yield a “yes”decision. Thus, in block 135, the line detection logic 70 increments therunning sum in the histogram for tap a.

However, now assume that the line detection logic 70 reads a value ofone-thousand-three-hundred (1300) instead of one-thousand-seven-hundred(1700) for tap a in block 131. In such an example, the absolute value ofthe difference between the tap's current and baseline tap coefficientsis three-hundred (300), which does not exceed the tap threshold of tapa. Thus, in block 123, the line detection logic 70 does not incrementthe running sum in the histogram for tap a.

As shown by the flowchart of FIGS. 6 and 7, the aforedescribed processmay be repeated over time. Note that the anomaly detection logic 70 maybe configured to take a sample periodically (e.g., every 30 seconds). Byrepeating the process of FIGS. 6 and 7 over time, the accuracy of thehistogram for estimating the location or locations of one or more lineanomalies increases. In this regard, anomaly indications are more likelyto occur for the taps 64 corresponding with anomaly locations. Indeed,in the present example, only one anomaly exists on line 25, and thelocation of this anomaly corresponds with tap a. Thus, by repeating theprocess of FIGS. 6 and 7, it is likely that the running sum for tap awill have the highest value in the histogram. Accordingly, by analyzingthe histogram, it is possible to predict the location of the anomaly.

Indeed, it is possible to establish a running sum threshold such thatany running sum of the histogram that exceeds the threshold indicates anexistence of a line anomaly at a line location corresponding to the tap64 associated with the running sum. The anomaly detection logic 70 maybe configured to analyze the histogram and to detect an anomaly for eachrunning sum that exceeds the running sum threshold. In the instantexample where there is only one anomaly, which is located at a locationcorresponding with tap a, the threshold is preferably set to a valuethat is below the running sum associated with tap a but is above each ofthe running sums of taps 64 corresponding to locations that are notclose to the anomaly location. Such a threshold may depend on a ratio ofthe histogram counts for each specific tap versus the total histogramcounts. In other embodiments, other methodologies for determining therunning sum threshold may be employed.

The second case of the telecommunication line anomaly detection,referred to herein as case two, is when the severity of the anomalyprevents the transceiver 23 from reaching synchronization altogether.FIG. 8 depicts an exemplary methodology that may be employed by theanomaly detection logic 70 in order to detect such an anomaly.

For the purposes of illustration, assume that the anomaly detectionlogic 70 is configured to track the coefficients of n number taps of theecho canceler 63, where n is any positive integer. Further assume that aparticular one of the taps 64, referred to hereafter as “tap a,”corresponds to a location on the telecommunication line 25 that is adistance “d” (FIG. 2) from the transceiver 23. In this regard, a changein the contact resistance of the telecommunication line 25 at a distanced from the transceiver 23 causes the tap coefficient of tap a to change.For the purposes of illustration, assume that a significantly degradedsplice is located at distance d from the transceiver 23, thereby causingthe resistivity of the line 25 at distance d from the transceiver 23 tosignificantly fluctuate over time resulting in an inability to reliablytrain and maintain a stable data mode signal. Also assume that there areno other degraded splices or other types of line anomalies on thetelecommunication line 25.

Similar to conventional-transceivers, the transceiver 23 may try toestablish communication settings, such as an initial set of tapcoefficients 66, for example, in a training mode and then communicatedata in a data mode that follows the training mode. If an anomaly on thetelecommunication line 25 is severe enough, the transceiver 23 maycontinuously try to train without ever attaining data mode, or it mayalternate between an unreliable data mode and training. In theembodiment, depicted by FIG. 8, steps are taken to detect line anomaliesduring training when the severity of the anomalies is such that reliabledata mode communication over the telecommunication line 25 is prevented.

During the training mode of the transceiver 23, there is a segment ofthe train used for the purpose of training the echo canceler 63. Thissegment of the train does not need as high a quality telecommunicationline to successfully train the echo canceler as is needed to maintain areliable data mode. In the case of the severe splice or line anomaly,the anomaly detection logic 70 may utilize the echo canceler tapcoefficients 66 after the echo canceler training segment of thetransceiver training sequence to detect the anomaly.

In block 201, the echo canceler 63 in the transceiver 23 trains until itproperly converges on a solution. In other methodologies, a signal errorvalue or other diagnostic may be evaluated to determine the level ofconvergence of the echo tap coefficients 66 for anomaly detection. Sincea valid set of tap coefficients 66 exists upon completion of block 201,the echo tap coefficients 66 are read and stored in block 205. In block209, the anomaly detection logic 70 determines whether a baseline set ofecho tap coefficients 88 already exists. If a “no” determination ismade, then the current echo canceler tap coefficients 66 are stored asthe baseline set of tap coefficients 88 in block 225, and the anomalydetection logic 70 exits the process depicted by FIG. 8. The transceiver23 will continue training and may either enter data mode or fail toattain data mode and retrain. For illustrative purposes, assume that thetap coefficient of tap a has a value of one-thousand (1000) upon a “no”determination in block 209. In such an example, the anomaly detectionlogic 70, in block 225, stores a value of one-thousand (1000) in memory75 as the baseline tap coefficient for tap a. Likewise, the other tapcoefficients 66 of the other taps 64 in existence may be used toestablish the other baseline tap coefficients 88.

If a “yes” determination is made in block 209, then a baseline set ofecho tap coefficients 88 already exists. In block 213 of FIG. 8, theanomaly detection logic 70 takes the current tap coefficients 66 thatwere read and stored in block 205 and compares these coefficients to thebaseline tap coefficients 88 in an effort to detect line anomalies. Inparticular, for each tap 64, the anomaly detection logic 70, in block213, subtracts the tap's current coefficient from its correspondingbaseline tap coefficient to compute a difference that indicates how muchthe coefficients of the tap 64 has changed since the last occurrence ofblock 225.

In block 217, the anomaly detection logic 70 detects possible lineanomalies. In particular, if none of the tap differences computed inblock 213 exceed the corresponding tap thresholds 85, then thecoefficients of the taps 64 have not changed by an amount large enoughto indicate a line anomaly may exist. If such a “no” determination ismade in block 217, then the anomaly detection logic 70 uses thecoefficients read in block 205 to update the baseline tap coefficients88, as described earlier, and the anomaly detection logic 70 exits theprocess depicted by FIG. 8. If a “yes” determination is made in block217, then at least one of the tap differences calculated in block 213exceeds the corresponding tap threshold 85 (i.e., the tap threshold 85associated with the same tap 64). This means that one or more of the tapcoefficients 66 has changed by a significantly large amount indicatingthat a line anomaly may exist.

If a “yes” determination is made in block 217, then the anomalydetection logic proceeds to block 221. The anomaly detection logic 70may maintain a histogram having a different running sum associated witheach tap 64. If a tap 64 has the largest difference between its currentcoefficient and its baseline coefficient than the other taps 64 and ifthat difference exceeds the corresponding tap threshold 85 in block 217,then the anomaly detection logic 70, in block 221, increments the tap'srunning sum. Thus, the running sum for a particular tap 64 indicates thetotal number of times that the anomaly detection logic 70 detected apossible line anomaly based on a comparison of the tap's coefficient inthe echo canceler 63 with the tap's baseline coefficient stored inmemory 75. In general, the higher the value of the tap's running sum,the more likely it is that a line anomaly, such as a degraded splice,exists at the location of the line 25 corresponding to the tap 64. Afterupdating the histogram in block 221, the anomaly detection logic 70 usesthe coefficients read in block 205 to update the baseline tapcoefficients 88 as described earlier, and the anomaly detection logic 70exits the process depicted by FIG. 8.

The process defined by the flowchart of FIG. 8 may be repeated each timethe transceiver trains or retrains. By repeating this process over time,the accuracy of the histogram for estimating the location or locationsof one or more line anomalies increases. In this regard, anomalyindications are more likely to occur for the taps 64 corresponding withanomaly locations. Indeed, in the present example, only one anomalyexists on line 25, and the location of this anomaly corresponds with tapa. Thus, by repeating the process of FIG. 8, it is likely that therunning sum for tap a will have the highest value in the histogram.Accordingly, by analyzing the histogram, it is possible to predict thelocation of the anomaly.

1. An anomaly detection system, comprising: an echo canceler having aplurality of taps respectively associated with a plurality of tapcoefficients; and anomaly detection logic configured to determine adifference between a new tap coefficient associated with one of the tapsand a previous tap coefficient associated with the one tap, the anomalydetection logic configured to perform a comparison between thedifference and a threshold and to detect an anomaly along atelecommunication line based on the comparison, wherein the anomalycauses a resistance at a point on the telecommunication line to varyover time.
 2. The system of claim 1, wherein the anomaly detection logicis configured to maintain a histogram of anomaly indications based oncomparisons of associated tap coefficients.
 3. The system of claim 1,wherein the anomaly detection logic is configured to maintain a runningsum of a total number of anomaly indications detected by the anomalydetection logic based on comparisons between tap coefficients associatedwith the one tap.
 4. The system of claim 3, wherein the anomalydetection logic is configured to compare the running sum to a threshold.5. The system of claim 1, wherein the anomaly detection logic isconfigured to perform a second comparison between a threshold and avalue indicative of an error rate associated with the telecommunicationline, the anomaly detection logic further configured to detect theanomaly based on the second comparison.
 6. The system of claim 5,wherein the value represents a minimum signal-to-noise ratio detectedduring a particular time period prior to the second comparison.
 7. Thesystem of claim 1, wherein the anomaly is a degraded splice along thetelecommunication line.
 8. The system of claim 1, wherein the anomalydetection logic is configured to indicate, based on the comparison, alocation of the anomaly on the telecommunication line.
 9. An anomalydetection system, comprising: an echo canceler having a plurality oftaps respectively associated with a plurality of tap coefficients; andanomaly detection logic configured to determine when at least one of thetap coefficients fluctuates by at least a specified amount and to detectan anomaly along a telecommunication line based on a detection, by thelogic, that the at least one tap coefficient fluctuated by at least thespecified amount.
 10. The system of claim 9, wherein the anomalydetection logic is further configured to maintain a running sumindicative of a number of times that the logic detects the at least onetap fluctuating by at least the specified amount, wherein the anomalydetection logic is configured to detect the anomaly based on the runningsum.
 11. The system of claim 10, wherein the anomaly detection logic isfurther configured to compare the running sum to a threshold.
 12. Thesystem of claim 9, wherein the anomaly is a telecommunication linesplice that is degrading communication occurring over thetelecommunication line between a transmitter at one end of thetelecommunication line and a receiver at another end of thetelecommunication line.
 13. The system of claim 12, wherein thedetection is based on a fluctuation of the tap coefficient while thetransmitter is communicating with the receiver over thetelecommunication line.
 14. The system of claim 13, wherein the anomalydetection logic is configured to indicate, based on the detection, alocation of the splice on the telecommunication line.
 15. An anomalydetection system, comprising: an echo canceler having a plurality oftaps respectively associated with a plurality of tap coefficients; andanomaly detection logic configured to establish a set of baseline tapcoefficients based on the tap coefficients, the anomaly detection logicconfigured to compute differences between new tap coefficients of theecho canceler and the baseline tap coefficients and to detect, based onthe differences, a time varying anomaly along a telecommunication lineat a junction of two sections of the telecommunication line.
 16. Thesystem of claim 15, wherein the anomaly detection logic is configured toperiodically update the baseline tap coefficients.
 17. The system ofclaim 15, wherein the anomaly detection logic is configured to performcomparisons between the differences and a plurality of thresholds, eachof the comparisons comparing a respective one of the differences and arespective one of the thresholds, wherein the anomaly detection logic isconfigured to detect the anomaly based on the comparisons.
 18. Thesystem of claim 17, wherein the anomaly detection logic is configured toupdate at least one of the baseline tap coefficients in response to oneof the comparisons.
 19. The system of claim 17, wherein the anomalydetection logic is configured to maintain a histogram of the results ofthe comparisons.
 20. An anomaly detection method, comprising the stepsof: determining a difference between a new tap coefficient associatedwith a tap of an echo canceler and a previous tap coefficient associatedwith the tap; comparing the difference to a threshold; and detecting ananomaly along a telecommunication line based on the comparing step, theanomaly causing a time varying change in a transmission characteristicof a point along the transmission line.
 21. An anomaly detection method,comprising the steps of: monitoring a plurality of tap coefficients ofan echo canceler; determining when at least one of the tap coefficientsfluctuates by at least a specified amount; and detecting an anomalyalong a telecommunication line based on the determining step, theanomaly causing a time varying change in resistance at a point along thetransmission line.
 22. The method of claim 21, further comprising thestep of maintaining a running sum indicating a number of times that theat least one tap coefficient fluctuates by at least the specifiedamount, wherein the detecting is further based on the running sum. 23.The method of claim 22, wherein the detecting step comprises the step ofcomparing the running sum to a threshold.
 24. An anomaly detectionmethod, comprising the steps of: establishing a set of baseline tapcoefficients based on a set of tap coefficients of an echo canceler;computing differences between the baseline tap coefficients and new tapcoefficients of the echo canceler; and detecting an anomaly along atelecommunication line based on the differences, the anomaly causing atime varying change in resistance at a junction of two sections of thetelecommunication line.
 25. The method of claim 24, further comprisingthe step of periodically updating the baseline tap coefficients.
 26. Themethod of claim 24, further comprising the step of comparing thedifferences to a plurality of thresholds, wherein the detecting step isfurther based on the comparing step.
 27. The method of claim 26, furthercomprising the step of maintaining a histogram of the results of thecomparing step, wherein said detecting step is further based on thehistogram.
 28. An anomaly detection method, comprising the steps of:establishing a set of baseline tap coefficients based on a set of tapcoefficients of an echo canceler; computing differences between thebaseline tap coefficients and new tap coefficients of the echo canceler;detecting an anomaly along a telecommunication line based on thedifferences; comparing the differences to a plurality of thresholds,wherein the detecting step is further based on the comparing step; andupdating at least one of the baseline tap coefficients in response to acomparison between one of the differences and one of the thresholds. 29.An anomaly detection system, comprising: an echo canceler having aplurality of taps respectively associated with a plurality of tapcoefficients; and anomaly detection logic configured to determine adifference between a new tap coefficient associated with one of the tapsand a previous tap coefficient associated with the one tap, the anomalydetection logic configured to perform a comparison between thedifference and a threshold and to detect an anomaly alone atelecommunication line based on the comparison, wherein the new tapcoefficient is based on a first digital signal transmitted from atransmitter at one end of the telecommunication line to a receiver atanother end of the telecommunication line, and wherein the previous tapcoefficient is based on a second digital signal transmitted from thetransmitter to the receiver.
 30. A system, comprising: a receivercoupled to a telecommunication line, the receiver configured to receivedigital signals transmitted from a remote transmitter via thetelecommunication line, the telecommunication line having a time varyinganomaly causing a resistance at a point on the telecommunication line tofluctuate over time thereby degrading the digital signals; and anomalydetection logic configured to detect the anomaly and to provide anindication of a location of the anomaly.
 31. The system of claim 30,wherein the anomaly detection logic is configured to detect the anomalybased on coefficients of an echo canceler.
 32. The system of claim 30,further comprising an echo canceler having a plurality of tapsrespectively associated with a plurality of tap coefficients, whereinthe anomaly detection logic is configured to perform a comparison of afirst tap coefficient associated with one of the taps and a second tapcoefficient associated with the one tap, the anomaly detection logicfurther configured to detect the anomaly based on the comparison.